AI Data Workflows

AI Data Workflows are a capability of unstructured data management platforms. AI and GenAI have created urgency on understanding and leveraging vast amounts of unstructured data within organizations. Despite the availability of free and low-cost AI tools, most enterprise data remains underutilized. This is problematic given the urgent need for AI in various sectors and since AI requires large amounts of unstructured data to deliver optimal results and to train its models.

AI Data Workflow Processes

AI data workflows can help automate two essential processes:

  • Discover, segment, classify and automate the movement of data to AI tools.
  • Enrich the metadata of unstructured data, which makes it easier to find and
    use in a variety of analytics and AI projects.

AI Data Workflows Capabilities

You’ll want the ability to search across vast data estates, ranging from terabytes to petabytes, to find relevant data. They ensure data governance by maintaining an audit trail and enforcing guardrails to ensure sensitive data is handled appropriately. To avoid high costs associated with AI’s pay-per-use models, it is vital to have a global index that tracks labels and tags, allowing users to search without reprocessing data. Read more about the Komprise Global File Index.

Automation is an important feature of AI data workflows technology because it ensures that AI models are continuously trained on the latest data without manual intervention. It also allows IT to incorporate policies into data workflows. Sample use cases for these workflows include, in the life sciences sector, querying data silos to find all data for a specific project, executing a function to identify a DNA mutation, tagging the data, and then moving it to a cloud AI service for analysis. The process ends with archiving the data once it is no longer needed. A marketing team could use an unstructured data management system to search across billions of images, tagging those that feature specific people or objects using tools like Amazon Rekognition, thereby saving significant manual effort.

AI data workflows are critical for unlocking the full potential of AI in organizations. By automating and streamlining data processes, ensuring compliance, and managing costs, organizations can harness AI to improve operations and outcomes across various sectors.

Learn more about the AI data workflow use case for Komprise Intelligent Data Management.

Learn more about Komprise Smart Data Workflow Manager for AI.

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